Sleep Efficiency May Predict Depression in a Large Population-Based Study

Abstract

Objectives:The purpose of our study was to investigate the effect of objective sleep characteristics on the incidence of depression.MethodsThe participants of our study (1,595 men and 1,780 women with 63.1 ± 10.7 years) were selected from the Sleep Heart Health Study (SHHS) datasets. Depression was defined as the first occurrence between SHHS visit 1 and visit 2. Objective sleep characteristics, including sleep efficiency (SE), wake after sleep onset (WASO), sleep fragmentation index (SFI) and arousal index (ArI), were monitored by polysomnography. Multivariable logistic regression was used to explore the relationship between sleep characteristics and depression.ResultsA total of 248 patients with depression (7.3%) were observed between SHHS visits 1 and 2. After adjusting for covariates, SE (odds ratio [OR], 0.891; 95% confidence interval [CI] 0.811–0.978; P = 0.016) and WASO (OR, 1.021; 95% CI 1.002–1.039; P = 0.026) were associated with the incidence of depression. Moreover, the relationship between SE and depression was more pronounced in men (OR, 0.820; 95% CI 0.711–0.946; P = 0.007) than in women (OR, 0.950; 95% CI 0.838–1.078; P = 0.429) in subgroup analysis (Pinteraction < 0.05).ConclusionsSE and WASO may be markers for the incidence of depression. The association between SE and depression was intensified in men.

Changes in sleep quality and sleep disturbances in the general population from before to during the COVID-19 lockdown: A systematic review and meta-analysis

“…Similarly, a prolonged sleep onset latency has been associated with metabolic syndrome ( 95 ), and with an increased risk of cardiovascular disease (CVD) ( 98 ), and depressive symptoms ( 99 ). Finally, poor sleep efficiency is associated with a higher risk of incident CVD ( 100 ) and depression ( 101 ). Almost all of the studies included in our systematic review reported an increase in sleep disturbances, consistently with two meta-analyses that found a higher prevalence of sleep disturbances during the lockdown with respect to non-lockdown periods ( 9 , 10 ).…”